Serial communication systems require the extraction of a sampling clock from a serial stream, where the clock harmonic is not intrinsic in the signal itself. This extraction is performed by a non-linear circuit called a Clock and Data Recovery (CDR) unit. The CDR is responsible for tracking low frequency phase changes in the signal by observing the transitions of the signal and performing averaging.
FIG. 2 illustrates a typical clock and data recovery (CDR) circuit 200 for recovering a clock signal and data from a data signal using a phase-locked loop (PLL). The CDR circuit 200 comprises a phase detector 202 which generates up or down pulses whose durations are proportional to the phase error between the recovered clock signal and the data signal. Outputs of the phase detector 202 are connected to a phase pump (charge pump) 204. The phase pump 204 is connected by a loop filter 206 to a voltage-controlled oscillator (VCO) 208 for charging the voltage-controlled oscillator 208 either “up” or “down” by a control voltage. This allows phase corrections of the clock signal provided by the voltage-controlled oscillator 208. The clock signal of the voltage-controlled oscillator 208 is fed back to a clock input of the phase detector 202 forming the phase-locked loop. The clock signal or the recovered clock signal is also fed back to a clock input of a data sampler 210 for sampling the data signal at the rate of the recovered clock signal and for providing recovered data at a data output thereof. The recovered clock signal is a timing signal generated synchronous to the rate at which the original data pulses were transmitted from a transmitter in a communication system. The data sampler 210 preferably comprises a D-type flip-flop with a data input, a clock input and a data output. The phase detector preferably also comprises D-type flip-flops.
For example, in an optical communication system, a CDR is designed to find a mean phase of the transitions between low and high levels of an optical signal based on long-term averaging of the transitions. FIG. 3 shows an example of the superposition of transmitted data signals 302, 304 received at a receiver of the communication system and having ideal transition characteristics and undistorted amplitudes yielding to a perfect crossover of the signals. Broken curves 302′, 304′ further illustrate the effect of jitter 306 e.g. clock or phase jitter on the transition behaviour of the signals. For detecting the transition of a signal from a high state to a low state or vice versa, the transitions are sampled at a decision level in the middle of an eye formed by the superposed signals. The lower half of FIG. 3 shows the Probability Distribution Function (PDF) 308 of detected transitions of signals which are subjected to jitter. From this distribution, the mean transition value of the detected transitions is easily derived to obtain a mean sampling point for the sampling of data contained in a data signal.
However, in a long-haul optical communication system, signal distortion leads to an eye of the received data signal that is not optimal for a CDR. The distortion of the optical signals is caused e.g. by the optical dispersion of a transmission fibre and by the switch on/switch off behaviour of a transmitter like a laser.
FIG. 4 shows an example of the superposition of distorted optical signals 402, 404. The crossover of the falling and the rising edges of the signals is no longer positioned in the middle of a peak-to-peak amplitude of the eye, but towards the zero level of the optical signal. In such a case, the probability distribution function 408 of the detected transitions using a decision level in the middle of the eye comprises two peaks. Each peak is associated to the jittered transition of a falling edge and to the jittered transition of a rising edge of a signal, respectively. The jitter is shown at 406. It is readily visible that here the determination of a mean transition value is not possible. Rather, the distribution of the transitions leads to a dead zone, where the CDR is no longer able to find the mean transition value of the data signal. Since the sampling of the data from the data signal is based on a correct predict of the mean transition value, an unstable phase value will lead to a wrong sample of the data eye, thus leading to a degradation in the bit error rate of the link.
Usually, only averaging the transitions of either the rising or the falling edge of a signal solves this problem. Now that only a single edge is detected, the probability distribution function no longer has a dead zone and shows the same distribution as a signal, wherein the decision level is positioned at the crossover. However, this method suffers from a reduction in the amount of phase error information provided to a phase-locked loop. As stated above, a CDR must track low-frequency wander, and its ability to achieve this is a function of the amount of phase error information available. By only using one edge of the data, half the information available to the CDR is lost, thus leading to a degradation of the tracking ability and an increase in the bit error rate of a receiver.
FIG. 5 shows another usual solution of the above problem in which the decision level of the CDR is simply adjusted to be at the crossover of the superposed data signals 502, 504. However, this solution suffers from the reduced signal-to-noise ratio of the transition amplitude, leading to false detection of transitions and false tracking of the signal. The reduced signal-to-noise ratio (S/N) is caused by the fact that due to the distortion of the signals, the crossover of the signals lies close to the low signal level which is strongly subjected to noise.